Strategy to Build a BigData Solution That Could Actually Work

BigData is nothing without big insight. And, when entire core is running after big-data hype, all everyone cares is getting their hands dirty with tools to get to those big-insights. But, the price to get to those big insights is bigger if not big. Businesses struggle a lot to get their lights up and running, let alone sleeping with one eye open of being run over by competition. So, why do all those awesome tools that radically change businesses rarely require minimal learning? Why tools are not build around ease of its use and adoption by businesses? We have learned this lesson while Business Intelligence wave hit the market and still, businesses struggle with making it work for them. And now, a new wave, which is 2.0 big data, is hitting the streets.

Yes, sure, currently available big-data tools are awesome. These tools could help businesses enormously. But the bigger question is, by when will the businesses be able to get this tools rolling to its full capacity. That too, without being hit by another wave of new technology staring at them as one looks at the antiques. Big-data adoption is low by businesses; only businesses with expendable resources were able to get going on this adoption. But for the rest, it’s still a big project for some other time and place.

BigData product managers could learn from this and help build products that could really compliment current businesses in their true sense and not suggest their way of doing things. This new product strategy should accommodate the shortfalls of current strategy & suggests something that could be up and ripe for mass adoption and not just open to a few brave who could really experiment and spend substantial time, money and resources in getting the tool running for their business.

As a starter, look at following 5 basic steps that could help in easy and early adoption:

1. Measure and Improve Time To Adoption: May be it’s the right time for product managers & clients to start capturing how much longer does it take for adopting a tool to it’s full capacity. This measure will help businesses and product managers in making sure there are not building something which is really further along when it comes to adoption and build something that could be readily integrated with current services and products. A product could start being high on Time To Adoption but could work it’s way downwards in making sure they build something which is easily adoptable by their prospective businesses. This metric will also help businesses understand which product is having its shortest route to their business.

2. Degree of adoption with existing resources: Another important metric for product managers and clients is to figure out how much of client’s existing infrastructure and resources will be utilized. This will keep the client’s interest and integration strategy in perspective. If the degree of adoption is higher, it means it is going to be a bit bumpy road for business integration and should be planned accordingly. On the other side, this will give product managers a key perspective into how to go about designing the product. The right product will make integration faster and offload client’s nightmare and adoption troubles.

3. Openness to other tools: Yes, it is nightmare to any product managers. Smart managers, will not take long in figuring out that it is better to be prepared than losing the battle with smarter competitor. If you product strategy believes in keeping clients hostage in your system, you should ignore it by all means. But if you care to grow with your clients, give it a long and hard look. An easily integratable tool will always find easy adaptability as well as more market share. At the end, you should know it is very difficult to be doing everything and let your client explore better alternatives as well. You need to stay in business because your product rocks not because your clients are stuck. This strategy will keep tool companies real and relevant. On the other side, client will not have nightmares to not adopt the best tool for their business if some other tool could compliment your offerings.

4. Time to Basic proficiency levels: This is another good indicator for measuring a good tool. Not to anyone’s surprise, this indicator will suggest how fast could one attain substantial knowledge to start using the tool. Product managers should monitor this metric and test it on various users and create benchmark. Product strategy should include improving upon the benchmark. This is suggesting how fast will the client be able to achieve the minimum proficiency to be using the product effectively. These metrics on the other side suggest clients that how much will they need to plan their resources for adoption. A longer learning cycle driven tools should be evaluated accordingly. This will also help product managers in building tool that could really speed up the adoption.

5. Data driven product strategy: One of my favorite area. It is to have data do the most of the talking and leaving minimum things for the gut to figure out. Having a data driven product approach will truly help build something, which is loved by clients and in-demand; which is closer to client’s problem and which is showing better return on investment for product managers as well as clients. Such metrics find it easy when it comes to selling to clients or using for budget approval. Such techniques will help product managers to be less risk driven and build something of sustained value. Client should ask more data centric questions when evaluating a product as well. This will promote a healthy discussion on what to expect from the product and have some idea on how the product is baked and what all are some important metrics product managers holds dear when considering their product design.

Certainly, these 5 steps are not the end, but just the beginning. The main idea is to communicate how product managers could align their design strategy to include client side metrics. This will ensure products are build with easy and faster adoption cycle. These 5 metrics could be benchmarked and segmented across various other vertices as well as for better and effective results. By including client side product usage metrics, you could build something effective and powerful. Something that could really help mass businesses gain access to the top of the line product without investing their years into adoption without much momentum.

Keep Calm & Get Hired!

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